引用本文: | 梁彦刚,郝道亮,唐国金.捷联导引头视线转率估计的交互式多模型样条滤波算法.[J].国防科技大学学报,2014,36(5):70-74.[点击复制] |
LIANG Yangang,HAO Daoliang,TANG Guojin.Spline filtering algorithm based on interacting multiple model for line-of-sight rate estimation in strap-down seeker system[J].Journal of National University of Defense Technology,2014,36(5):70-74[点击复制] |
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捷联导引头视线转率估计的交互式多模型样条滤波算法 |
梁彦刚, 郝道亮, 唐国金 |
(国防科技大学 航天科学与工程学院,湖南 长沙 410073)
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摘要: |
针对捷联导引头测量信息的弹目惯性视线转率估计,提出了一种基于交互式多模型算法的样条滤波方法(IMM-SF)。基于体视线和惯性视线的映射关系解算惯性视线角,将其作为虚拟观测量进行滤波,设置多个过程噪声模型,每个模型分别采用样条滤波器进行滤波,IMM-SF滤波器的估值结果为各滤波器估值的加权综合。该方法不必对目标的未知机动建模,应用更加方便,并且可在交互式多模型算法的框架下自适应地调整滤波器的噪声。Monte-Carlo仿真结果表明该方法可有效估计视线转率,并可提高估值精度。 |
关键词: 虚拟观测量 视线转率估计 样条滤波 交互式多模型 |
DOI:10.11887/j.cn.201405012 |
投稿日期:2014-01-19 |
基金项目:国家自然科学基金资助项目(11372345)、973计划资助项目(2013CB733100) |
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Spline filtering algorithm based on interacting multiple model for line-of-sight rate estimation in strap-down seeker system |
LIANG Yangang, HAO Daoliang, TANG Guojin |
(College of Aerospace Science and Engineering,National University of Defense Technology, Changsha 410073, China)
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Abstract: |
A spline filtering algorithm based on interacting multiple model algorithm (IMM-SF) was proposed to estimate Line-of-sight (LOS) rate in strap-down seeker system. Based on the mapping relation between body LOS and inertial LOS, the inertial LOS angles were obtained and used as virtual observed data of filters. A set of process noise models were set up, and every model worked independently based on the spline filter. The valuation output of IMM-SF was the weighted composition of the valuation outputs of all parallel spline filters. By using this method, the unknown maneuver models of the target were no longer indispensable, which makes the method more convenient to use. Process noise could be adaptively adjusted under the configuration of IMM. The Monte-Carlo simulation results show that the LOS rate can be estimated effectively based on SF-IMM, which can also improve the accuracy of estimation. |
Keywords: virtual observed data LOS rate estimation spline filtering interacting multiple model |
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